1. Joint Modeling
1.1 Trace plots for convergence check
The current MCMC setting is:
- 100,000 iteration;
- 90,000 burn-in;
- 10 thinning.
1.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.01 1.02
## LDevsum 1.00 1.01
## dl0 1.06 1.18
## dl1 1.03 1.08
##
## Multivariate psrf
##
## 1.07
1.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
1.4 WAIC results
| LevelH | LevelL | |
|---|---|---|
| DIC | 12343.3428 | 33821.3570 |
| DIC3 | 12406.2875 | 33901.4359 |
| PWAIC | 92.9698 | 162.8667 |
| WAIC | 12411.1078 | 33906.4019 |
2. Separate Modeling
2.1 Trace plots for convergence check
The current MCMC setting is:
- 100,000 iteration;
- 90,000 burn-in;
- 10 thinning.
2.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.01 1.04
## LDevsum 1.00 1.02
## dl0 1.19 1.48
## dl1 1.09 1.25
##
## Multivariate psrf
##
## 1.16
2.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
2.4 WAIC results
| LevelH | LevelL | |
|---|---|---|
| DIC | 12343.33287 | 33819.8974 |
| DIC3 | 12404.25581 | 33901.3866 |
| PWAIC | 90.42995 | 162.5199 |
| WAIC | 12408.11394 | 33905.4610 |